Computational Analysis of Routine Biopsies Improves Diagnosis and Prediction of Cardiac Allograft Vasculopathy.

ABSTRACT:

Background

Cardiac allograft vasculopathy (CAV) is a leading cause of morbidity and mortality for heart transplant recipients. Although clinical risk factors for CAV have been established, no personalized prognostic test exists to confidently identify patients at high versus low risk of developing aggressive CAV. This investigation aimed to leverage computational methods for analyzing digital pathology images from routine endomyocardial biopsies (EMBs) to develop a precision medicine tool for predicting CAV years before overt clinical presentation.

Methods

Clinical data from 1 year after transplant were collected on 302 transplant recipients from the University of Pennsylvania, including 53 patients with early-onset CAV and 249 no early-onset CAV controls. These data were us

SUBMITTER: Peyster EG 

PROVIDER: S-EPMC9133227 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature